# Стенд-проверка (stage-2) · промт оператора:

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 10,
  "verdict": "Implemented Tail-Weighted Optimal Batch Scheduling on the structurally matched tabular Friedman#1 regression track with the shared mlp_tiny architecture and a local variable-batch Adam loop. Across 8 paired seeds, the idea was significantly worse than the tuned fixed-batch baseline: paired delta +2.933495 MSE, permutation p=0.0081, and 0/8 wins. The mechanism signature is unconfirmed because the run did not quantitatively correlate per-step trained-model noise estimates with sqrt(c_t s_t).",
  "metrics": {
    "baseline": "Tuned fixed-batch Adam, lr=0.006 and batch=32: 8-seed test MSE mean 6.988916, SD 0.402721.",
    "idea": "Tail-weighted variable-batch Adam, lr=0.006 and per-epoch example budget 8000: 8-seed test MSE mean 9.922412; batch range 41–128, mean 62.5; paired delta +2.933495, p=0.0081."
  },
  "bench_report": {
    "bench_version": 1,
    "track": "tabular",
    "model": "mlp_tiny",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.006,
        "batch": 32
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.0015,
            "batch": 32
          },
          "mean": 12.079814672470093
        },
        {
          "cfg": {
            "lr": 0.0015,
            "batch": 64
          },
          "mean": 16.354594945907593
        },
        {
          "cfg": {
            "lr": 0.003,
            "batch": 32
          },
          "mean": 8.110420823097229
        },
        {
          "cfg": {
            "lr": 0.003,
            "batch": 64
          },
          "mean": 13.231624126434326
        },
        {
          "cfg": {
            "lr": 0.006,
            "batch": 32
          },
          "mean": 6.854706883430481
        },
        {
          "cfg": {
            "lr": 0.006,
            "batch": 64
          },
          "mean": 9.873589992523193
        }
      ],
      "full": {
        "mean": 6.988916456699371,
        "std": 0.40272099288824403,
        "per_seed": [
          6.72859001159668,
          6.984129428863525,
          6.906972408294678,
          6.799135684967041,
          6.242666721343994,
          7.195944786071777,
          7.462729454040527,
          7.591163158416748
        ],
        "n": 8
      }
    },
    "idea": {
      "best_cfg": {
        "lr": 0.006,
        "batch_budget": 8000
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.006,
            "batch_budget": 8000
          },
          "mean": 9.922411799430847,
          "per_seed": [
            8.689536094665527,
            11.649765014648438,
            9.706146240234375,
            9.317113876342773,
            8.459336280822754,
            9.973560333251953,
            11.035902976989746,
            10.547933578491211
          ]
        },
        {
          "cfg": {
            "lr": 0.0015,
            "batch_budget": 8000
          },
          "mean": 16.83699667453766,
          "per_seed": [
            15.854043006896973,
            16.610029220581055,
            18.131574630737305,
            14.799296379089355,
            15.572802543640137,
            16.681474685668945,
            17.97016716003418,
            19.07658576965332
          ]
        },
        {
          "cfg": {
            "lr": 0.003,
            "batch_budget": 8000
          },
          "mean": 13.589162349700928,
          "per_seed": [
            12.75110912322998,
            14.062518119812012,
            13.924327850341797,
            12.308281898498535,
            12.10305404663086,
            13.396442413330078,
            14.798388481140137,
            15.369176864624023
          ]
        }
      ],
      "mean": 9.922411799430847,
      "per_seed": [
        8.689536094665527,
        11.649765014648438,
        9.706146240234375,
        9.317113876342773,
        8.459336280822754,
        9.973560333251953,
        11.035902976989746,
        10.547933578491211
      ]
    },
    "comparison": {
      "delta_mean": 2.933495342731476,
      "idea_wins": 0,
      "n_pairs": 8,
      "per_seed_diffs": [
        1.9609460830688477,
        4.665635585784912,
        2.7991738319396973,
        2.5179781913757324,
        2.2166695594787598,
        2.777615547180176,
        3.5731735229492188,
        2.956770420074463
      ],
      "p_value": 0.0081,
      "mde": 0.712641190380764,
      "mde_rel_pct": 10.196733568014638,
      "verdict": "idea worse (significant)",
      "system_worked": false
    },
    "mechanism_signature": {
      "predicted_vs_observed": {
        "predicted_relative_weight_mean": 1.0,
        "observed_batch_mean": 62.5,
        "batch_min": 41,
        "batch_max": 128,
        "quantitative_match_tested": false
      },
      "confirmed": false,
      "note": "Observed batch range is not a quantitative test of sqrt(c_t s_t); per-step trained-model noise estimates and correlation were not recorded, so the mechanism prediction is unconfirmed."
    }
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py",
  "files": [
    "stage2_bench.py",
    "bench_report.json",
    "bench_run.log"
  ],
  "limitations": "Only the structurally matched tabular track was tested; vision, sequence, and dynamics were not tested. Wall-clock speed, memory, and a rigorous per-step trained-model noise-to-weight correlation were not measured. The report is saved at bench_report.json.",
  "system_verdict": "failed",
  "practical_verdict": "harms",
  "mechanism_ok": 0,
  "system_judged": true
}